In order to compare and analyze the capability of Himawari-8 geostationary meteorological satellite products in retrieving fire spot in different regions, the statistical data of fire spot in Shandong from 2017 to 2019 and the multi-channel monitoring data of satellite are selected to analyze the effectiveness of adaptive threshold recognition algorithm in Shandong Province. With respect to the brightness temperature of background T3.9bg, brightness temperature differente in background window ΔT3.9_11bg, and the background coefficients of n1 and n2, the parameters sensitivity test of the underlying surface of forest and grass is carried out, and the recognition effectiveness is tested by selecting the threshold intervention algorithm. The results are as follows. 1) Adaptive threshold algorithm can continuously conduct multi-time detection of fire spots in Shandong, the number of which shows obvious seasonal variations, and the recognition accuracy is 71.5%. 2) In the 4 parameter experiments, the trend of recognition accuracy of different underlying surface types is similar, but it is sensitive to the change of threshold value. 3) The average accuracy rates of the threshold intervention algorithm for forest land and grassland fire spot recognition are 72.7% and 81.6%, respectively, which are 5.8% and 3.8% higher than those of the original algorithm. 4) The recognition algorithm of threshold intervention can effectively filter misjudged pixels, but both of them have missed areas. Optimizing threshold setting according to the local underlying surface attributes can effectively improve the accuracy of fire spot recognition.